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Research Data Management Introduction: EUDAT/Open AIRE Webinar| |


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| | Research Data Management Introduction: EUDAT/Open AIRE Webinar- May2016

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Research Data Management Introduction: EUDAT/Open AIRE Webinar| |

  1. 1. Research Data Management - an introductory webinar Tony Ross-Hellauer, OpenAIRE Sarah Jones, EUDAT This work is licensed under the Creative Commons CC-BY 4.0 licence
  2. 2. Open Access Infrastructure for Research in Europe Who we are Research Data Services, Expertise & Technology
  3. 3. • Why manage data? • RDM in Horizon 2020 (+ recent changes) • How to manage and share research data? • EUDAT and OpenAIRE services Overview
  4. 4. WHY MANAGE DATA? Image CC-BY-NC-SA by Leo Reynolds
  5. 5. Data explosion • More and more data is being created • Issue is not creating data, but being able to navigate and use it • Data management is critical to make sure data are well-organised, understandable and reusable
  6. 6. Digital data are fragile and susceptible to loss for a wide variety of reasons • Natural disaster • Facilities infrastructure failure • Storage failure • Server hardware/software failure • Application software failure • Format obsolescence • Legal encumbrance • Human error • Malicious attack • Loss of staffing competencies • Loss of institutional commitment • Loss of financial stability • Changes in user expectations Data loss Image CC BY-NC-SA 2.0 by Dave Hill
  7. 7. A reproducibility crisis
  8. 8. Why manage data? • Make your research easier • Stop yourself drowning in irrelevant stuff • Save data for later • Avoid accusations of fraud or bad science • Share your data for re-use • Get credit for it • Meet funder/institution requirements Because well-managed data opens up opportunities for re-use, sharing and makes for better science!
  9. 9. RDM IN HORIZON 2020 Image “Open Data” CC BY 2.0 by
  10. 10. EC Open Research Data Pilot, Jan 2015 - • A limited, voluntary pilot (initially 8 programme areas) with opt-out and safeguards • Participating projects must: • Keep a data management plan, to be updated at regular intervals • Deposit in an open access repository: 1. the data, including associated metadata, needed to validate the results presented in scientific publications as soon as possible; 2. other data, including associated metadata, as specified and within the deadlines laid down in the data management plan
  11. 11. EC Open Research Data Pilot Opt-out Reasons the-pilot-in-the-first-calls-of-horizon-2020
  12. 12. Just announced! H2020 - Open Data by Default from 2017
  14. 14. CREATING DATA PROCESSING DATA ANALYSING DATA PRESERVING DATA GIVING ACCESS TO DATA RE-USING DATA Research data lifecycle CREATING DATA: designing research, DMPs, planning consent, locate existing data, data collection and management, capturing and creating metadata RE-USING DATA: follow- up research, new research, undertake research reviews, scrutinising findings, teaching & learning ACCESS TO DATA: distributing data, sharing data, controlling access, establishing copyright, promoting data PRESERVING DATA: data storage, back- up & archiving, migrating to best format & medium, creating metadata and documentation ANALYSING DATA: interpreting, & deriving data, producing outputs, authoring publications, preparing for sharing PROCESSING DATA: entering, transcribing, checking, validating and cleaning data, anonymising data, describing data, manage and store data Ref: UK Data Archive:
  15. 15. • Findable – assign persistent IDs, provide rich metadata, register in a searchable resource... • Accessible – Retrievable by their ID using a standard protocol, metadata remain accessible even if data aren’t... • Interoperable – Use formal, broadly applicable languages, use standard vocabularies, qualified references... • Reusable – Rich, accurate metadata, clear licences, provenance, use of community standards... FAIR data
  16. 16. A DMP is a brief plan to define: • how the data will be created? • how it will be documented? • who will access it? • where it will be stored? • who will back it up? • whether (and how) it will be shared & preserved? DMPs are often submitted as part of grant applications, but are useful whenever researchers are creating data. Data Management Plans
  17. 17. DMPonline A web-based tool to help researchers write DMPs Includes a template for Horizon 2020 Guidance from EUDAT and OpenAIRE being added
  18. 18. • Metadata and documentation is needed to locate and understand research data • Think about what others would need in order to find, evaluate, understand, and reuse your data. • Get others to check the metadata to improve quality • Use standards to enable interoperability Metadata & documentation
  19. 19. Metadata standards Use relevant standards for interoperability
  20. 20. Where to store data? • Your own drive (PC, server, flash drive, etc.) – And if you lose it? Or it breaks? • Somebody else’s drive / departmental drive • “Cloud” drive – Do they care as much about your data as you do? • Large scale infrastructure services like EUDAT
  21. 21. How to backup? • 3... 2... 1... backup! – at least 3 copies of a file – on at least 2 different media – with at least 1 offsite • Use managed services where possible e.g. University filestores or infrastructure services like EUDAT rather than local or external hard drives • Ask IT teams for advice
  22. 22. Backup and preservation – not the same thing! • Backups – Used to take periodic snapshots of data in case the current version is destroyed or lost – Backups are copies of files stored for short or near-long-term – Often performed on a somewhat frequent schedule • Archiving – Used to preserve data for historical reference or potentially during disasters – Archives are usually the final version, stored for long-term, and generally not copied over – Often performed at the end of a project or during major milestones
  23. 23. Data repositories • Does your publisher or funder suggest a repository? • Are there data centres or databases for your discipline? • Does your university offer support for long-term preservation?
  24. 24. A mistake in a spreadsheet led to dramatically different results from those published. These results were cited by the International Monetary Fund and the UK Treasury to justify austerity programmes. Had the data been shared, this could have been picked up earlier. The importance of sharing data
  25. 25. Concerns about data sharing Concern Solution inappropriate use due to misunderstanding of research purpose or parameters security and confidentiality of sensitive data lack of acknowledgement / credit loss of advantage when competing for research funding
  26. 26. Concerns about data sharing Concern Solution inappropriate use due to misunderstanding of research purpose or parameters security and confidentiality of sensitive data lack of acknowledgement / credit loss of advantage when competing for research funding metadata metadata metadata metadata
  27. 27. Concerns about data sharing Concern Solution inappropriate use due to misunderstanding of research purpose or parameters provide rich Abstract, Purpose, Constraints and Supplemental Information where needed security and confidentiality of sensitive data • the metadata does NOT contain the data • Use Constraints specify who may access the data and how lack of acknowledgement / credit specify a required data citation within the Use Constraints loss of data insight and competitive advantage when vying for research funding create second, public version with generalised Data Processing Description
  28. 28. Make data shareable • Create robust metadata that has been checked • Include reference information in metadata e.g. unique IDs & properly formatted data citations • Publish your metadata so it’s discoverable. Use portals, clearing houses, online resources… • Package up the data and associated metadata to deposit in repositories • License the data clearly
  29. 29. Licensing research data This DCC guide outlines the pros and cons of each approach and gives practical advice on how to implement your licence CREATIVE COMMONS LIMITATIONS NC Non-Commercial What counts as commercial? ND No Derivatives Severely restricts use These clauses are not open licenses Horizon 2020 Open Access guidelines point to: or
  30. 30. EUDAT licensing tool Answer questions to determine which licence(s) are appropriate to use
  31. 31. What to preserve & share It’s not possible to keep everything. Select based on: – What has to be kept e.g. data underlying publications – What can’t be recreated e.g. environmental recordings – What is potentially useful to others – What has scientific, cultural or historical value – What legally must be destroyed How to select and appraise research data:
  32. 32. EUDAT & OPENAIRE SERVICES Image CC-BY-NC ‘Data centre’ by Bob Mical
  33. 33. EUDAT services EUDAT offers a pan-European solution, providing a generic set of services to ensure minimum level of interoperability Building common data services in close collaboration with 25+ communities
  34. 34. EUDAT B2 service suite Covering both access and deposit, from informal data sharing to long-term archiving, and addressing identification, discoverability and computability of both long- tail and big data, EUDAT’s services will address the full lifecycle of research data
  35. 35. CREATING DATA PROCESSING DATA ANALYSING DATA PRESERVING DATA GIVING ACCESS TO DATA RE-USING DATA PIDs  Referencing data: Finding data and making data findable Data Transfer from public data servers Store mutable data Accessing services Move data to HPC
  36. 36. OpenAIRE services: For all content types! With GitHub integration! Upload Describe Publish Create communities!
  37. 37. Link data to publications
  38. 38. OpenAIRE training and support materials • Briefing papers, factsheets, Webinars, workshops, FAQs • Information on: • Open Research Data Pilot • Creating a data management plan • Selecting a data repository
  39. 39. Thanks – any questions? Contact us: Tony Ross-Hellauer, OpenAIRE: Sarah Jones, EUDAT: Acknowledgements: Thanks to EUDAT colleagues Mark van de Sanden and Christine Staiger for slides. Content has also been repurposed from the DataONE Educational modules, ‘Data Management’ and ‘Data Sharing’ Retrieved from